In many geologic basins the detailed identification and characterization of faults, folds, and other structural or geometric characteristics can be extremely useful in basin and reservoir characterization analysis. The size scale of these analyses range from identification of regional dip-domains on a scale of 1's to 100's of kilometers to the dip of individual reflectors on the scale of 10's to 100's of meters. Regional dip is useful in the analysis of hydrocarbon migration and systems analysis, while individual reflector dip is useful for the purposes of fault-seal or dip-steering applications. All size scales benefit from a quantitative characterization across the entire volume of seismic data.
There are two main approaches for obtaining dip information from seismic data. The first approach is manual seismic geometry mapping. Manual delineation of seismic geometries in seismic data can be a time consuming, subjective, and difficult process. This approach is burdened with associated costs and trade-offs in cycle-time, potential subjectivity, and density of observations. The second approach is the use of dip and azimuth calculations based on cross-correlations. However, techniques based on cross-correlation algorithms are prone to noise, limited in resolution, and computationally expensive. As a result, trade-offs in quality and scalability limitations must be made.
Several techniques have been used in the oil industry to automate and further quantify the production of seismic dip information. D. B. Neff, in U.S. Pat. No. 6,092,025 entitled “Hydrocarbon Edge Detection Using Seismic Amplitude” and issued Jul. 18, 2000, describes a cross-correlation based technique for the production of strike and dip volumes. The technique finds points corresponding to the maximum cross-correlations in a 3×3 moving sub-volume of traces, and calculates a best fit plane to these points to obtain the strike and dip of this plane. The limitations of this technique include the reliance on a cross-correlation/plane-fitting algorithm that is computationally expensive and potentially noise prone.
Research Disclosure Serial No. 294073 published on Oct. 10, 1988, entitled “Horizon Processing Techniques for Recognition of Structural Geology on 3D Seismic” describes a method in which the gradient dT/dx (i.e. the dip) of a pre-existing horizon is analyzed for the identification of faults, flexures, or other structural and stratigraphic features. However, the method requires a pre-existing horizon and does not generate three-dimensional volumes of strike and dip measures.
Randen, T., Monsen, E., Signer, C., Abrahamsen, A., Hansen, J., Saeter, T., Schlaf, J., and Sonneland, L. present a method for dip-steered seismic facies analysis in “Three-Dimensional Texture Attributes for Seismic Data Analysis”, 70th Annual SEG Int. Mtg, Calgary, Canada, Aug. 6-11, 2000, Expanded Abstr. Biogr., Vol. 1, pp 668-671. The method produces dip and azimuth cubes using a fully 3D gradient estimation approach which, combined with a principal component analysis, produces the dip and azimuth estimates. This approach is computationally intensive and also suffers from potentially reduced resolution in the estimates.
Meldahl, P., Heggland, R., de Groot, P. F. M., and Bril, A. H., have two relevant publications, “The Chimney Cube, an Example of Semi-Automated Detection of Seismic Objects by Directive Attributes and Neural Networks: Part I; Methodology”, and “The Chimney Cube, an Example of Semi-Automated Detection of Seismic Objects by Directive Attributes and Neural Networks: Part II; Interpretation” in 69th Annual SEG Int. Mtg, Houston, Oct. 31-Nov. 5, 1999, Expanded Abstr. Biogr. Vol. 1, pp. 931-934, Pap No. SINT2 3, and a patent application, GB 9819910.0 “Method of Seismic Body Recognition”, all of which involve dip-steered textural attributes consistent with the cross-correlation and full 3D-gradient based methods outlined above.
Dip-steering applications are an important supporting technology to many other interpretative techniques. The stratigraphic framework of any particular geologic setting is an important aspect that is always considered, albeit unconsciously, by seismic facies interpreters. Seismic facies interpreters, for example, do not consider continuity solely in the time plane. Rather, they judge continuity following the stratigraphic layering defined by dip of seismic reflectors.
Dip steering is particularly important to discontinuity related calculations. For example, Marfurt, K. J. and Kirlin, R. L, “3-D Broad-Band Estimates of Reflector Dip and Amplitude”, Geophysics, Vol. 65, No. 1, pp 304-320, Jan-Feb, 2000, and Bahorich, Farmer, Kirlin, and Marfurt, “Identifying structural and stratigraphic features in three dimensions—such that seismic signal processing and exploration give improved resolution, computational speed and estimates of dip even with coherent noise,” patent WO 9713166, describe a cross-correlation-based technique for discontinuity estimates that first applies a pre-defined dip azimuth measurement axis to remove a significant portion of the regional structural dip. They then apply a semblance calculation as a function of time to multiple seismic traces to further estimate and correct for local dip. During this step, they also create a maximum semblance cube that highlights stratigraphic and structural discontinuities, corrected for structural dips. The main objectives of these methods and techniques are the production of cross-correlation, semblance, or discontinuity measures. However, a by-product is a dip and azimuth cube. The main disadvantage of their correlation/eigenvalue-based method to produce dip and azimuth cubes is that it is very computationally intensive.
Similarly, Marfurt, Gersztenkorn, Nissen, Sudhaker, and Crawford, Geophysics, Vol. 64, No. 1, pp 104-111, January-February 1999, “Coherency Calculations in the Presence of Structural Dip,” examine the similarity of multiple traces at various time lags to estimate the dip of reflectors. An eigenstructure algorithm is then used to calculate the similarity of traces in the locally averaged dip direction. The main disadvantage of this approach is the reliance on cross-correlation calculations, which are computationally expensive.
The abstract published by Alekseev, A. S., and Burmakov, Y. A., “Determination of Spatial Parameters of Reflecting Surfaces in the Three-Dimensional Seismics” Dokl Akad Nauk SSSR, Vol. 253, No. 6, pp 1339-1342, 1980, describes a method for dip and curvature characterization of seismic reflectors in 3D seismic data. However, this method is also cross-correlation based.
Thus, there is a need to generate, in a computationally efficient manner, a process that enables the rapid, quantitative characterization of seismic data so that it can be exploited in the geologic mapping/reservoir characterization process. Computational efficiency dictates that the process depend neither upon the picking of horizons, either manually by interpreters or automatically by computers, nor upon the calculation of cross correlations.